TR-Dizin İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/396
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Research Project Biyonik Elin Faaliyete Hazırlanmasında Kaldırılacak Cisme dair Ağırlık Algısının Beyin Sinyalleriyle Belirlenmesi(2022) Ulutabanca, Halil; Altindis, Fatih; Unal, Ramazan; Yilmaz, Bulent; Sarrafıkhosrowshah, MahsaThe upper extremity prostheses vary due to the patient?s articulation level and the methods used to move them. There are prostheses that are either cosmetic, or that work with shoulder movement (mechanical), or controlled by myoelectronic and electroencephalography (EEG) signals. However, intuitive and unnatural control of the prosthesis places a great mental burden on the user. In this project, the aim is to develop a system to improve the control of the bionic hand prosthesis by using EEG and EMG signals together, by making use of the user's visual weight perception. With this system, it is aimed to reduce the physical and mental burden/discomfort patients may experience while using a mechanical prosthesis. The preconditioning of the prototype hand to be produced is provided by evaluating the weight of the objects seen by the patients to the extent that the brain perceives them visually. In this way, the force exerted by the patient on the shoulder while holding the object will decrease and the mental load will be alleviated. For this purpose, EEG and electromyography (EMG) signals of the subjects were taken and processed, and then a real-time implementation was developed. In the first stage, a study was conducted that aimed to operate the prosthesis by using the motor intention waves of the prosthesis users and the classification success of the machine learning approaches (detection of the intention to activate the prosthesis) was examined by taking EEG data from 30 healthy participants. In the second stage, EEG and EMG signals of 31 healthy participants were recorded synchronously while reaching for the object, lifting the object and leaving the object in the starting position. After the features of these signals were determined, it was determined that the object was heavy, medium weight or light using various classification approaches. In parallel with biosignal processing studies, prosthetic hand and wrist designs and three- dimensional prints were obtained. It is aimed to use the shoulder movement to open and close the prosthetic hand, and to control the wrist stiffness, to process the biosignals and drive a tiny motor with high torque with the automatic decision produced. In addition, the characterization of the prosthesis was made. As a result of the classification of the multi-channel EEG signals from 20 healthy individuals with Fourier-based synchrosequeezing transform (FSST) and singular value decomposition (SVD) approaches by extracting features, the goal was to control the stiffness of the wrist part of the prosthesis. As a result, it was possible for the system to detect the weight of the object the user sees while employing the prosthesis and to precondition the prosthesis according to this weight when they want to hold and move that object.Research Project Biyonik Elin Faaliyete Hazırlanmasında Kaldırılacak Cisme Dair Ağırlık Algısının Beyin Sinyalleriyle Belirlenmesi(2022) Ulutabanca, Halil; Altindis, Fatih; Unal, Ramazan; Yilmaz, Bulent; Sarrafıkhosrowshah, MahsaThe upper extremity prostheses vary due to the patient?s articulation level and the methods used to move them. There are prostheses that are either cosmetic, or that work with shoulder movement (mechanical), or controlled by myoelectronic and electroencephalography (EEG) signals. However, intuitive and unnatural control of the prosthesis places a great mental burden on the user. In this project, the aim is to develop a system to improve the control of the bionic hand prosthesis by using EEG and EMG signals together, by making use of the user's visual weight perception. With this system, it is aimed to reduce the physical and mental burden/discomfort patients may experience while using a mechanical prosthesis. The preconditioning of the prototype hand to be produced is provided by evaluating the weight of the objects seen by the patients to the extent that the brain perceives them visually. In this way, the force exerted by the patient on the shoulder while holding the object will decrease and the mental load will be alleviated. For this purpose, EEG and electromyography (EMG) signals of the subjects were taken and processed, and then a real-time implementation was developed. In the first stage, a study was conducted that aimed to operate the prosthesis by using the motor intention waves of the prosthesis users and the classification success of the machine learning approaches (detection of the intention to activate the prosthesis) was examined by taking EEG data from 30 healthy participants. In the second stage, EEG and EMG signals of 31 healthy participants were recorded synchronously while reaching for the object, lifting the object and leaving the object in the starting position. After the features of these signals were determined, it was determined that the object was heavy, medium weight or light using various classification approaches. In parallel with biosignal processing studies, prosthetic hand and wrist designs and three- dimensional prints were obtained. It is aimed to use the shoulder movement to open and close the prosthetic hand, and to control the wrist stiffness, to process the biosignals and drive a tiny motor with high torque with the automatic decision produced. In addition, the characterization of the prosthesis was made. As a result of the classification of the multi-channel EEG signals from 20 healthy individuals with Fourier-based synchrosequeezing transform (FSST) and singular value decomposition (SVD) approaches by extracting features, the goal was to control the stiffness of the wrist part of the prosthesis. As a result, it was possible for the system to detect the weight of the object the user sees while employing the prosthesis and to precondition the prosthesis according to this weight when they want to hold and move that object.Article Thermosensitive Pluronic® F127-Based in Situ Gel Formulation Containing Nanoparticles for the Sustained Delivery of Paclitaxel(2023) Unal, Sedat; Aktas, Yesim; Doğan, Osman; Tekeli, Merve CelikBone metastasis is one of the most encountered complications among cancer patients and majority of cancer types has led to bone metastasis. Paclitaxel (PCX) is an anticancer agent commonly used in cancer treatment. However, its clinical use is restricted owing to poor water solubility. PCL NPs were investigated to cope with solubility problem of PCX. The size, polydispersity index and zeta potential of PCL were 383.8±2.4 nm, 0.253±0.122 and +51.3±6.1 mV, respectively. The PCX encapsulation efficiency was 77.2±2.1%. Subsequently, in situ gellling system was prepared by using different Pluronic F-127 concentration in order to determine the optimum ratio. İn situ gel formulation containing 20% Pluronic F-127 was selected as the optimum formulation and subjected to characterization tests. The viscosity of in situ gelling system with CS/PCX-PCL NPs at room temperature (25 °C±0.1) and at body temperature (37 °C±0.1) were found 137.00 ±3.05 cP and 890.30 ±89.61 cP at 100 rpm, respectively. According to the release results, in situ gel provided prolonged release profile compared to PCL NPs alone. Consequently, in situ gel containing CS/PCX-PCL NP elucidated in detail is a promising approach for locally applicable injectable systems.Article Citation - WoS: 4Citation - Scopus: 4All-Polymer Ultrasonic Transducer Design for an Intravascular Ultrasonography Application(Tubitak Scientific & Technological Research Council Turkey, 2019-07-26) Hah, DooyoungIntravascular ultrasonography (IVUS), a medical imaging modality, is used to obtain cross-sectional views of blood vessels from inside. In IVUS, transducers are brought to the proximity of the imaging targets so that high-resolution images can be obtained at high frequency without much concern of signal attenuation. To eliminate mechanical rotation rendered in conventional IVUS, it is proposed to manufacture a transducer array on a flexible substrate and wrap it around a cylindrical frame. The transducer of consideration is a capacitive micromachined ultrasonic transducer (CMUT). The whole device needs to be made out of polymers to be able to endure a high degree of bending (radius: 1 mm) Bending of the devices leads to considerable changes in the device characteristics, including resonant frequency and pull-in voltage due to geometrical dimension changes and stress induced. The main purpose of this work is to understand the effect of bending on the device characteristics by means of finite element analysis. Another objective of the work is to understand the relationships between such an effect and the device geometries. It is learned that the bending-induced stress depends strongly on anchor width, membrane thickness, and substrate thickness. It is also learned that resonant frequency and pull-in voltage become lower in most cases because of using a flexible substrate in comparison to those of the device on a rigid substrate. Bending-induced stress increases the spring constant and hence increases resonant frequency and pull-in voltage, although this effect is relatively weaker. For most of the device geometries, pull-in voltage is too high for the polymer material to endure. This is the main drawback of the all-polymer CMUT. In order to meet the design goal of 20 MHz resonant frequency, the membrane radius has to be smaller than 7.7 mu m for a thickness of 3 mu m.